Video Reports

Link to this video

Get LinkLicensePrint
Bookmark and Share

By Ruth Saldanha | 06-06-2019

How to invest in familiar names

Investing in known names brings a sense of comfort - here's how to create a screen for them - Morningstar CPMS' Emily Halverson-Duncan takes a U.S. dividend approach


Emily Halverson-Duncan: Welcome to Quant Concepts. With the U.S. market housing a vast offering of companies to invest in, it's no wonder investors can get overwhelmed by the number of unfamiliar names. Many people feel a certain sense of comfort investing in companies who at a minimum have names they can recognize. Typically, the most familiar names tend to be larger companies as they are more likely to have frequent media coverage and products and services that are commonly used by the average person.

Today, I'm going to showcase a strategy which invests in U.S. dividend stocks within the S&P 500. This index will serve as our universe of better known companies and help us avoid those unfamiliar names. So, let's take a look at how to build that strategy.

First off, as mentioned, our universe is going to be the S&P 500. So, we are eliminating any other U.S. companies in the CPMS universe. From there, we are going to rank that universe of 500 names. A couple of the factors we are going to rank on; expected dividend yields, so what a company is expected to be paying out. That's going to have a higher impact on how a stock is ranked. So, a higher dividend yield would mean the stock is ranked higher on the list. A lower dividend yield means it's ranked lower. Another factor here; five-year dividend growth. So, five-year dividend growth is looking at an annualized number of how a company is growing their dividends across the long-term.

After we've ranked our stocks 1 to 500, we are going to screen out the stocks that we don't want to own so we end up with the list of stocks we are willing to buy. A couple of the factors we are using here to screen; we are looking at an expected dividend yield greater than or equal to 2%. So, anything below that would be removed from the list. A three-month earnings per share estimate revision greater than or equal to minus 5%. So, what that's looking at is across the last three months earnings per share estimates, how they are revised. And so, if they are revised downward more than 5%, then we wouldn't be purchasing that stock.

On the flipside, when we are going to sell stocks, our rules here are the expected dividend yield if it falls below 1%, again, we're buying if it's above 2%; but if it falls too low, we are going to sell it out of the model. And again, that three-month earnings per share estimate revision, if that falls below minus 15%.

Now that we've built our strategy, we want to go in and see of course how it performs historically. So, we are going to run a back test. Our back test is going to be run from December 1993 to end of April 2019. We're going to hold 15 names and invest $1 million to start. So, let's go ahead and give that a run.

Okay. So, the model actually did quite well. 12.9% annualized and that's beating the benchmark by about 3.2%. Turnover was very low at 38%. Again, turnover is just looking at how often you're going to be trading the stocks out of the portfolio. So, at 38% it means of those 15 stocks you're probably trading less than half on average in a given year.

So, let's take a look at some of the names that are in the model right now. If we look at what was held at the end of April 2019, we can see some pretty well-known U.S. names such as

Starbucks, obviously a well-known coffee brand; Broadcom, Texas Instruments and a number of other names that are pretty familiar.

So, changing the universe of the S&P 500 really limits out the unfamiliar stocks in the U.S. and ends you up with the numbers of ones that would be much more familiar to the average investor.

For Morningstar, I'm Emily Halverson-Duncan.

{1}
{1}
{2}